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\title{An Anytime Oversubscription Path Planner for Autonomous
  Underwater Vehicles}

\author{}
%  \authorblockN{Jnaneshwar Das\authorrefmark{1}, Thom
%     Maughan\authorrefmark{2}, Mike McCann\authorrefmark{2}, Mike
%     Godin\authorrefmark{2}, \\ Tom~O'Reilly\authorrefmark{2}, Monique Messi\'e\authorrefmark{2},  Fred
%     Bahr\authorrefmark{2}, Kevin Gomes\authorrefmark{2}, Fr\'ed\'eric Py\authorrefmark{2}, \\
%     Jim Bellingham\authorrefmark{2},  Gaurav S. Sukhatme\authorrefmark{1},   Kanna Rajan\authorrefmark{2}}
%   \authorblockA{\authorrefmark{1}Robotic Embedded Systems Laboratory,
%     Department of Computer Science, University of Southern
%     California\\} 
%     \textit{\{jnaneshd,gaurav\}@usc.edu}
%  \authorblockA{\authorrefmark{2}Monterey Bay Aquarium Research
%     Institute, Moss Landing, California\\}
% \textit{\{tm,mccann,godin,oreilly,monique,flbahr,kgomes,fpy,jgb,kanna.rajan\}@mbari.org}}

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\begin{document}
\maketitle
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\begin{abstract}

  This paper describes work to allow an Autonomous Underwater Vehicle
  (AUV) to navigate within a pre-defined planar roadmap to tackle a
  set of mission goals all of which may not be feasible for
  execution. The method uses results from an all-pairs shortest path
  calculation to estimate costs for traversal employing
  steepest-ascent hill climbing to identify a feasible subset of goals
  that have high utility and low cost. It employs chronological
  backtracking heuristic search in a constraint-based temporal
  planning paradigm to insert goals into the plan in the order of
  traversal to ensure compliance with other system constraints. The
  algorithm is integrated into an intelligent executive, which handles
  dispatch, monitoring, and repair of the plan as execution unfolds.

\end{abstract}

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\section{Acknowledgments}

MBARI authors are supported by a block grant from the David and
Lucille Packard Foundation. We thank the crew of the R/V \emph{Zephyr}
for their valuable support.

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